MétaCan
Menu
Back to cohort
Record W4399092423 · doi:10.1364/oe.525614

Observation of THz surface waves escaping from metal gratings through a dielectric substrate

2024· article· en· W4399092423 on OpenAlexaff
Hong Qi, Jinfeng Yang, Y. W. Wang, Zihao Yang, Jiaming Zhang, Kosaku Kato, Makoto Nakajima, Dazhi Li, Cheng-Ying Tsai, Zhengzheng Liu, Jian Wang, Kuanjun Fan

Bibliographic record

VenueOptics Express · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGyrotron and Vacuum Electronics Research
Canadian institutionsNexen (Canada)
FundersNational Key Research and Development Program of ChinaJapan Society for the Promotion of ScienceNational Natural Science Foundation of China
KeywordsTerahertz radiationOpticsGratingFemtosecondDielectricMaterials sciencePhysicsRadiationSurface waveTransition radiationOptoelectronicsLaser

Abstract

fetched live from OpenAlex

Extensive research has been conducted on generating THz waves using Smith-Purcell radiation, yet a portion of the electron bunch's interaction energy with the gratings is confined to the metal gratings' surface, leading to a low THz radiation power. This paper experimentally demonstrates that metal gratings with a dielectric substrate can emit the resonant modes in surface waves when excited by relativistic femtosecond electron bunches. The observed spectra of the resonant THz waves align well with the theoretical estimations derived from the configuration's dispersion relation and 3D simulations. In comparison to traditional Smith-Purcell radiation generated by the grating, these resonant THz waves exhibit significantly higher intensity and improved orientation. Additionally, we investigated the radiation characteristics of the resonant THz waves, including radiation angle, beam-grating distance, beam energy, and bunch length. This innovative approach presents a novel method for generating high-power coherent terahertz radiation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.301
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueOptics ExpressSame topicGyrotron and Vacuum Electronics ResearchFrench-language works237,207